The term “spectrum analyzer” refers to a device used to examine the spectral composition of a radio frequency (RF) input signal. A typical spectrum analyzer will allow a user to select a frequency span defined by a span center frequency and a span width. The typical spectrum analyzer will then divide the frequency span into segments (“bins”) and for each frequency bin in the span, measure input signal energy associated with frequencies in the bin. The result is typically shown on a visual display as a graph with the frequencies of the span on the horizontal axis and the input signal energy per bin on the vertical axis. The RF input signal may comprise one or more component signals at different frequencies, each displayed as a peak on the vertical axis.
A digital spectrum analyzer typically consists of several sections, including an RF section, a local oscillator (LO) section, an intermediate frequency (IF) section, a digital processing section and a display. The RF section typically includes an attenuator to reduce the RF input signal amplitude, one or more stages of mixers to convert the RF input signal to an intermediate frequency (IF) signal using local oscillator signals from one or more local oscillators (LO) in the LO section. The IF signal has several components. A desired component is a frequency shifted version of the input RF. The IF signal will also have undesired components, including residual, spurious and image signals. The IF section typically has a system of filtering the IF signal to eliminate out-of-band signals, including IF signal components that are frequency shifted replicas of RF signal components that were not in the selected span and including some of the unwanted residual, spurious and image signals. The IF section also typically has an analog to digital converter for converting the analog IF signal to a set of digitized IF signal samples. The digital processing section typically has hardware or software for performing additional filtering, for performing Fast Fourier Transforms (FFT) of the time domain set of digitized IF signal samples to a frequency domain set of digitized IF signal samples and for making various measurements of the digital time and frequency domain sets of the IF signal samples.
Spectrum analyzers generate undesired residual, spurious and image signals. Residual signals are false signals that are displayed with no input into the spectrum analyzer, and are typically generated from the electronic circuitry of the spectrum analyzer itself. Spurious signals (“spurs”) are false signal products that result when an input signal is applied. Image signals are the undesired one of a summed frequency signal and a difference frequency signal, both of which are generated when mixing the RF input signal with an LO signal.
To minimize the introduction of unwanted residual signals, a spectrum analyzer typically isolates the LO, RF, IF and digital processing sections using shielding, which adds considerable weight and cost. Spectrum analyzers often use a Yttrium Iron Garnet (YIG) LO, which requires several watts of power and is expensive, but provides a clean signal which adds minimal phase noise to the input signal.
Measuring receivers are used to measure precise relative signal amplitude measurements over a wide dynamic range, measure peak and average modulation characteristics and apply filters to the IF analog and digital signals. Frequency modulation and amplitude modulation characteristics may be measured. Precise amplitude steps may be measured as well. Measuring receivers are typically separate devices from spectrum analyzers, in spite of sharing many functional blocks.
Many modern spectrum analyzers use the Fast Fourier Transform (FFT) technique to convert time-domain signal data into frequency-domain signal data. Processing high-resolution FFTs quickly requires a powerful processor.
Handheld spectrum analyzers contain less expensive, less accurate components, have less shielding and consume less power than a traditional rack-mount spectrum analyzer. They typically have a low resolution display and buttons for a user interface. They are generally not capable of processing automated commands and are of minimal usefulness in a lab setting. They generally have slower processors which are not capable of quickly processing very large FFTs. With less accurate components, less powerful processors and less shielding, handheld spectrum analyzers do a poor job of reducing residual, spurious and image signals and have poorer overall results than a larger, high quality spectrum analyzer.
RF cables are often used to connect spectrum analyzers to a signal being measured and can be a major source of measurement inaccuracies. RF cables typically have unknown, frequency-dependent losses which change as the cable is bent or twisted. It is often not very convenient to place a large spectrum analyzer near the source of an RF signal or orient it in such a way to minimize bending of the RF cables.
Owning a modern spectrum analyzer with good specifications is currently cost prohibitive for many students, inventors, and amateur radio enthusiasts.
What is needed is an ultra-low-cost, low-power, lightweight, portable spectrum analyzer similar in size and weight to a traditional RF power sensor; a spectrum analyzer that can be connected close to the source of a signal being measured without long intervening RF probe cables yet carries the signal processing power of the modern personal computer.